Volumetric imaging devices such as CT scanners are often used to recognize or detect particular objects of interest. For example, when using security scanners, objects of interest usually include threat materials, while in a medical setting objects of interest might be pathological tissue, such as cancer cells. The imaging device typically uses a segmentation algorithm to extract object representations from images. In a security scanner setting, a segmented object defines a collection of voxels for a detected luggage item. The properties of the segmented object are then extracted and used by the discrimination framework to identify threats. During segmentation, sometimes more than one object in the image may be grouped together and appear as a single object known as a compound object.
A compound object can be made up of two or more distinct items. Because the compound object actually comprises separate physical objects, properties of the compound object may not be able to be effectively compared with those of known threat and/or non-threat items. As such, for example, luggage containing a compound object may unnecessarily be flagged for additional (hands-on) inspection because the properties of the compound object resemble properties of a known threat object. Alternatively, a compound object that should be flagged as a threat may not be so identified because properties of a potential threat object in the compound object are diluted by the properties of one or more other (non-threat) objects in the compound object, and these diluted properties (of the compound object) more closely resemble those of a non-threat object than those of a threat object.